A genetic programming method for the identification of signal peptides and prediction of their cleavage sites

  • Authors:

  • David Lennartsson;Peter Nordin

  • Affiliations:

  • Saida Medical AB, Stena Center, Göteborg, Sweden;Department of Physical Resource Theory, Chalmers University of Technology, Göteborg, Sweden

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2004

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Abstract

A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN) approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.